Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "46" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460015 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.831559 | -0.638068 | -0.270808 | -1.052066 | 0.189988 | -0.335298 | 0.445521 | -0.125575 | 0.5961 | 0.6120 | 0.3556 | nan | nan |
| 2460014 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.016928 | -0.226833 | -0.479559 | -1.175784 | 0.008683 | -0.073539 | -0.874741 | -1.176818 | 0.5709 | 0.5909 | 0.3638 | nan | nan |
| 2460013 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.799450 | -0.607093 | -0.259086 | -0.911229 | -0.208460 | -0.497635 | -0.185785 | -0.680666 | 0.5909 | 0.6131 | 0.3642 | nan | nan |
| 2460012 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.817628 | -0.612661 | -0.437623 | -1.033933 | -0.290995 | -0.526664 | -0.304635 | -0.889583 | 0.5929 | 0.6133 | 0.3571 | nan | nan |
| 2460011 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.874364 | -0.570346 | -0.809434 | -1.227347 | -0.681473 | -1.301953 | 0.077168 | -0.777561 | 0.5899 | 0.6091 | 0.3635 | nan | nan |
| 2460010 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.200784 | -0.609174 | -0.709848 | -0.927384 | 0.003082 | -0.489850 | -0.278430 | -0.758965 | 0.5990 | 0.6207 | 0.3691 | nan | nan |
| 2460009 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.798256 | -0.432851 | -0.491126 | -1.194775 | -0.154136 | -0.527165 | -0.577909 | -0.488405 | 0.6007 | 0.6219 | 0.3753 | nan | nan |
| 2460008 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.060988 | -0.590766 | -0.752686 | -1.303264 | -0.660283 | -0.368490 | 0.177551 | -1.506616 | 0.6496 | 0.6678 | 0.3305 | nan | nan |
| 2460007 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.762823 | -0.315877 | -0.494144 | -1.216032 | -0.061709 | -0.470350 | -0.225560 | -0.756101 | 0.6097 | 0.6315 | 0.3584 | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 89.14% | 85.71% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.1656 | 0.1819 | 0.0808 | nan | nan |
| 2459998 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.678825 | -0.086664 | -0.359431 | -0.967467 | -0.336524 | -0.226984 | 0.157270 | -0.328979 | 0.6112 | 0.6353 | 0.3882 | nan | nan |
| 2459997 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.950978 | -0.229793 | -0.455621 | -0.914832 | -0.218809 | -0.453425 | 0.195263 | -0.683748 | 0.6292 | 0.6529 | 0.3922 | nan | nan |
| 2459996 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.698157 | 0.003281 | -0.042782 | -1.071829 | -0.159468 | -0.557608 | -0.039444 | -0.573267 | 0.6322 | 0.6526 | 0.4032 | nan | nan |
| 2459995 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.977832 | -0.017672 | -0.603869 | -1.129365 | -0.606824 | -0.312402 | -0.399108 | -0.871402 | 0.6296 | 0.6538 | 0.3889 | nan | nan |
| 2459994 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.907880 | 0.091541 | -0.581361 | -1.088196 | -0.610866 | -0.219692 | -0.688942 | -0.952847 | 0.6236 | 0.6458 | 0.3870 | nan | nan |
| 2459993 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.076982 | 0.301688 | -0.839944 | -0.937525 | -0.631978 | 0.162891 | -0.568482 | -1.018747 | 0.6205 | 0.6553 | 0.3978 | nan | nan |
| 2459991 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.430249 | -0.024121 | -0.721184 | -0.939180 | -0.364616 | -0.029319 | -0.487940 | -0.831601 | 0.6210 | 0.6386 | 0.3912 | nan | nan |
| 2459990 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.968664 | -0.001932 | -0.722332 | -0.864160 | -0.298128 | -0.119879 | 0.152691 | -0.374245 | 0.6265 | 0.6463 | 0.3914 | nan | nan |
| 2459989 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.920294 | -0.060937 | -0.667990 | -0.824172 | -0.410057 | -0.207907 | -0.168138 | -0.392525 | 0.6234 | 0.6453 | 0.3948 | nan | nan |
| 2459988 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.032417 | 0.212249 | -0.834318 | -0.895323 | -0.301892 | -0.786723 | -0.643858 | -0.961752 | 0.6193 | 0.6398 | 0.3852 | nan | nan |
| 2459987 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.861492 | 0.023572 | -0.758738 | -1.042251 | -0.266246 | -0.014071 | 0.115544 | -0.275789 | 0.6302 | 0.6505 | 0.3816 | nan | nan |
| 2459986 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.082526 | 0.153137 | -0.800668 | -0.950864 | -0.383593 | -0.223738 | 0.499185 | -0.845677 | 0.6383 | 0.6605 | 0.3429 | nan | nan |
| 2459985 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.778811 | 0.198046 | -0.675687 | -1.071288 | -0.472635 | -0.394320 | -0.078297 | -0.782468 | 0.6216 | 0.6406 | 0.3862 | nan | nan |
| 2459984 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.250072 | 0.239958 | -0.596529 | -0.966830 | 0.538169 | -0.408055 | 0.787634 | -0.231919 | 0.6394 | 0.6577 | 0.3649 | nan | nan |
| 2459983 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.015315 | 0.062418 | -0.665231 | -0.885847 | -0.486521 | -0.332465 | -0.081674 | -1.325460 | 0.6522 | 0.6790 | 0.3197 | nan | nan |
| 2459982 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.473407 | -0.373027 | -0.391449 | -1.165706 | -0.300784 | -0.221905 | 0.165969 | -1.043637 | 0.6945 | 0.7011 | 0.2944 | nan | nan |
| 2459981 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.082799 | -0.054481 | -0.894752 | -0.855077 | -0.879471 | -0.387947 | -0.797371 | -1.072594 | 0.6238 | 0.6447 | 0.3853 | nan | nan |
| 2459980 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.011381 | 0.007176 | -0.846707 | -1.205532 | -0.622431 | -0.307625 | -0.131141 | -1.380468 | 0.6694 | 0.6848 | 0.3145 | nan | nan |
| 2459979 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.324455 | -0.119931 | -0.976926 | -1.176639 | -0.416703 | -0.151709 | -0.538188 | -0.765184 | 0.6158 | 0.6403 | 0.3863 | nan | nan |
| 2459978 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.242949 | -0.073218 | -0.994887 | -1.066822 | -0.541032 | -0.383645 | -0.229672 | -0.366862 | 0.6169 | 0.6396 | 0.3949 | nan | nan |
| 2459977 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.122941 | -0.001042 | -0.835383 | -1.145485 | -0.040998 | -0.550848 | -0.457960 | -0.894603 | 0.5847 | 0.6073 | 0.3555 | nan | nan |
| 2459976 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.213733 | 0.023463 | -0.913475 | -1.138875 | -0.176919 | -0.325664 | -0.190833 | -0.413078 | 0.6311 | 0.6512 | 0.3869 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.445521 | -0.638068 | -0.831559 | -1.052066 | -0.270808 | -0.335298 | 0.189988 | -0.125575 | 0.445521 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Variability | 0.008683 | -1.016928 | -0.226833 | -0.479559 | -1.175784 | 0.008683 | -0.073539 | -0.874741 | -1.176818 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | -0.185785 | -0.799450 | -0.607093 | -0.259086 | -0.911229 | -0.208460 | -0.497635 | -0.185785 | -0.680666 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Variability | -0.290995 | -0.817628 | -0.612661 | -0.437623 | -1.033933 | -0.290995 | -0.526664 | -0.304635 | -0.889583 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.077168 | -0.874364 | -0.570346 | -0.809434 | -1.227347 | -0.681473 | -1.301953 | 0.077168 | -0.777561 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Variability | 0.003082 | -1.200784 | -0.609174 | -0.709848 | -0.927384 | 0.003082 | -0.489850 | -0.278430 | -0.758965 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Variability | -0.154136 | -0.798256 | -0.432851 | -0.491126 | -1.194775 | -0.154136 | -0.527165 | -0.577909 | -0.488405 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.177551 | -0.590766 | -1.060988 | -1.303264 | -0.752686 | -0.368490 | -0.660283 | -1.506616 | 0.177551 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Variability | -0.061709 | -0.762823 | -0.315877 | -0.494144 | -1.216032 | -0.061709 | -0.470350 | -0.225560 | -0.756101 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.157270 | -0.678825 | -0.086664 | -0.359431 | -0.967467 | -0.336524 | -0.226984 | 0.157270 | -0.328979 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.195263 | -0.950978 | -0.229793 | -0.455621 | -0.914832 | -0.218809 | -0.453425 | 0.195263 | -0.683748 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.003281 | -0.698157 | 0.003281 | -0.042782 | -1.071829 | -0.159468 | -0.557608 | -0.039444 | -0.573267 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.017672 | -0.977832 | -0.017672 | -0.603869 | -1.129365 | -0.606824 | -0.312402 | -0.399108 | -0.871402 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.091541 | -0.907880 | 0.091541 | -0.581361 | -1.088196 | -0.610866 | -0.219692 | -0.688942 | -0.952847 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.301688 | -1.076982 | 0.301688 | -0.839944 | -0.937525 | -0.631978 | 0.162891 | -0.568482 | -1.018747 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.024121 | -1.430249 | -0.024121 | -0.721184 | -0.939180 | -0.364616 | -0.029319 | -0.487940 | -0.831601 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.152691 | -0.001932 | -0.968664 | -0.864160 | -0.722332 | -0.119879 | -0.298128 | -0.374245 | 0.152691 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.060937 | -0.060937 | -0.920294 | -0.824172 | -0.667990 | -0.207907 | -0.410057 | -0.392525 | -0.168138 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.212249 | 0.212249 | -1.032417 | -0.895323 | -0.834318 | -0.786723 | -0.301892 | -0.961752 | -0.643858 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.115544 | -0.861492 | 0.023572 | -0.758738 | -1.042251 | -0.266246 | -0.014071 | 0.115544 | -0.275789 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.499185 | 0.153137 | -1.082526 | -0.950864 | -0.800668 | -0.223738 | -0.383593 | -0.845677 | 0.499185 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.198046 | 0.198046 | -0.778811 | -1.071288 | -0.675687 | -0.394320 | -0.472635 | -0.782468 | -0.078297 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.787634 | -0.250072 | 0.239958 | -0.596529 | -0.966830 | 0.538169 | -0.408055 | 0.787634 | -0.231919 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.062418 | -1.015315 | 0.062418 | -0.665231 | -0.885847 | -0.486521 | -0.332465 | -0.081674 | -1.325460 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | ee Temporal Discontinuties | 0.165969 | -0.473407 | -0.373027 | -0.391449 | -1.165706 | -0.300784 | -0.221905 | 0.165969 | -1.043637 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.054481 | -0.054481 | -1.082799 | -0.855077 | -0.894752 | -0.387947 | -0.879471 | -1.072594 | -0.797371 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.007176 | 0.007176 | -1.011381 | -1.205532 | -0.846707 | -0.307625 | -0.622431 | -1.380468 | -0.131141 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.119931 | -1.324455 | -0.119931 | -0.976926 | -1.176639 | -0.416703 | -0.151709 | -0.538188 | -0.765184 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.073218 | -0.073218 | -1.242949 | -1.066822 | -0.994887 | -0.383645 | -0.541032 | -0.366862 | -0.229672 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | -0.001042 | -1.122941 | -0.001042 | -0.835383 | -1.145485 | -0.040998 | -0.550848 | -0.457960 | -0.894603 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 46 | N05 | RF_maintenance | nn Shape | 0.023463 | 0.023463 | -1.213733 | -1.138875 | -0.913475 | -0.325664 | -0.176919 | -0.413078 | -0.190833 |